Evidence map›Paper›PMID 17987056›Full record

ReviewHeredity2008

Advances in Bayesian multiple quantitative trait loci mapping in experimental crosses.

N Yi, D Shriner

Abstract readReview
In one paragraph

Review in Heredity, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
  2. Article
  3. QTL fine mapping with Bayes C(π): a simulation study.Genetics, selection, evolution : GSE · 2013
    Article
  4. An integrated hierarchical Bayesian model for multivariate eQTL mapping.Statistical applications in genetics and molecular biology · 2012
    Article
  5. Article
  6. In silico genotyping of the maize nested association mapping population.Molecular breeding : new strategies in plant improvement · 2011
    Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Look before you leap: a new approach to mapping QTL.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2009
    Article
  14. Article
  15. Article
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

N YiSection on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. nyi@ms.soph.uab.edu
D Shriner

Funding

Bayesian Methods for Mapping Complex Epistatic GenesR01GM069430 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI YI, NENGJUN · 2005 to 2013
$2.3M
NIGMS NIH HHS GM069430NIGMS NIH HHS R01 GM069430
6 · The paper itself

Abstract

Many complex human diseases and traits of biological and/or economic importance are determined by interacting networks of multiple quantitative trait loci (QTL) and environmental factors. Mapping QTL is critical for understanding the genetic basis of complex traits, and for ultimate identification of genes responsible. A variety of sophisticated statistical methods for QTL mapping have been developed. Among these developments, the evolution of Bayesian approaches for multiple QTL mapping over the past decade has been remarkable. Bayesian methods can jointly infer the number of QTL, their genomic positions and their genetic effects. Here, we review recently developed and still developing Bayesian methods and associated computer software for mapping multiple QTL in experimental crosses. We compare and contrast these methods to clearly describe the relationships among different Bayesian methods. We conclude this review by highlighting some areas of future research.

Indexed as

Bayes TheoremModels, StatisticalSoftwareChromosome MappingCrosses, GeneticLikelihood FunctionsQuantitative Trait Loci

Identifiers

PMID17987056
PMCPMC5003624

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.